Construction of Immune-Related Diagnostic Model for Latent Tuberculosis Infection and Active Tuberculosis

Abstract

Zhihua Zhang,1 Yuhong Wang,2 Yankun Zhang,3 Shujun Geng,2 Haifeng Wu,4 Yanxin Shao,5 Guannan Kang6 1Department of Science & Education, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, People’s Republic of China; 2Department of Tuberculosis, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, People’s Republic of China; 3Department of Ophthalmology, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, People’s Republic of China; 4Clinical Laboratory, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, People’s Republic of China; 5Office of Clinical Pharmacological Center, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, People’s Republic of China; 6Department of Tuberculosis, Hebei Chest Hospital, Shijiazhuang, People’s Republic of ChinaCorrespondence: Yanxin Shao, Office of Clinical Pharmacological Center, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, No. 372, Sheng Li North Street, Shijiazhuang, Hebei, 050041, People’s Republic of China, Email [email protected]: Tuberculosis (TB) is one of the most infectious diseases caused by Mycobacterium tuberculosis (M. tb), and the diagnosis of active tuberculosis (TB) and latent TB infection (LTBI) remains challenging.Methods: Gene expression files were downloaded from the GEO database to identify the differentially expressed genes (DEGs). The ssGSEA algorithm was applied to assess the immunological characteristics of patients with LTBI and TB. Weighted gene co-expression network analysis, protein-protein interaction network, and the cytoHubba plug-in of Cytoscape were used to identify the real hub genes. Finally, a diagnostic model was constructed using real hub genes and validated using a validation set.Results: Macrophages and natural killer cells were identified as important immune cells strongly associated with TB. In total, 726 mRNAs were identified as DEGs. MX1, STAT1, IFIH1, DDX58, and IRF7 were identified as real hub immune-related genes. The diagnostic model generated by the five real hub genes could distinguish active TB from healthy controls or patients with LTBI.Conclusion: Our study may provide implications for the diagnosis and drug development of M. tb infections.Keywords: tuberculosis, latent tuberculosis infection, mycobacterium tuberculosis, immune, diagnostic model

Keywords

• tuberculosis
• latent tuberculosis infection
• mycobacterium tuberculosis
• immune
• diagnostic model